18 code implementations • 16 Aug 2017 • Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang
In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN).
Ranked #4 on Image Classification on Fashion-MNIST
5 code implementations • 17 Apr 2019 • Chao Li, Zhiyuan Liu, Mengmeng Wu, Yuchi Xu, Pipei Huang, Huan Zhao, Guoliang Kang, Qiwei Chen, Wei Li, Dik Lun Lee
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.
Ranked #1 on Information Retrieval on Amazon
2 code implementations • CVPR 2018 • Weijian Deng, Liang Zheng, Qixiang Ye, Guoliang Kang, Yi Yang, Jianbin Jiao
To this end, we propose to preserve two types of unsupervised similarities, 1) self-similarity of an image before and after translation, and 2) domain-dissimilarity of a translated source image and a target image.
1 code implementation • Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops 2020 • Wenhe Liu, Guoliang Kang, Po-Yao Huang, Xiaojun Chang, Yijun Qian, Junwei Liang, Liangke Gui, Jing Wen, Peng Chen
We propose an Efficient Activity Detection System, Argus, for Extended Video Analysis in the surveillance scenario.
6 code implementations • 21 Aug 2018 • Yang He, Guoliang Kang, Xuanyi Dong, Yanwei Fu, Yi Yang
Therefore, the network trained by our method has a larger model capacity to learn from the training data.
2 code implementations • CVPR 2019 • Guoliang Kang, Lu Jiang, Yi Yang, Alexander G. Hauptmann
Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while manual annotations are only available in the source domain.
Ranked #7 on Domain Adaptation on Office-31
1 code implementation • ECCV 2018 • Xiaolin Zhang, Yunchao Wei, Guoliang Kang, Yi Yang, Thomas Huang
A stagewise approach is proposed to incorporate high confident object regions to learn the SPG masks.
Ranked #1 on Weakly-Supervised Object Localization on ILSVRC 2015
1 code implementation • CVPR 2021 • Guangrui Li, Guoliang Kang, Yi Zhu, Yunchao Wei, Yi Yang
To better exploit the intrinsic structure of the target domain, we propose Domain Consensus Clustering (DCC), which exploits the domain consensus knowledge to discover discriminative clusters on both common samples and private ones.
Ranked #4 on Partial Domain Adaptation on Office-31
1 code implementation • ECCV 2020 • Guangrui Li, Guoliang Kang, Wu Liu, Yunchao Wei, Yi Yang
The target of CCM is to acquire those synthetic images that share similar distribution with the real ones in the target domain, so that the domain gap can be naturally alleviated by employing the content-consistent synthetic images for training.
Ranked #12 on Semantic Segmentation on GTAV-to-Cityscapes Labels
1 code implementation • NeurIPS 2020 • Guoliang Kang, Yunchao Wei, Yi Yang, Yueting Zhuang, Alexander G. Hauptmann
The conventional solution to this task is to minimize the discrepancy between source and target to enable effective knowledge transfer.
Ranked #25 on Synthetic-to-Real Translation on SYNTHIA-to-Cityscapes
2 code implementations • NeurIPS 2021 • Gengwei Zhang, Guoliang Kang, Yi Yang, Yunchao Wei
Directly performing cross-attention may aggregate these features from support to query and bias the query features.
Ranked #52 on Few-Shot Semantic Segmentation on COCO-20i (5-shot)
1 code implementation • ICCV 2019 • Qianyu Feng, Guoliang Kang, Hehe Fan, Yi Yang
In this paper, we exploit the semantic structure of open set data from two aspects: 1) Semantic Categorical Alignment, which aims to achieve good separability of target known classes by categorically aligning the centroid of target with the source.
1 code implementation • ICCV 2023 • Gengwei Zhang, Liyuan Wang, Guoliang Kang, Ling Chen, Yunchao Wei
The goal of continual learning is to improve the performance of recognition models in learning sequentially arrived data.
1 code implementation • 23 Apr 2023 • Cilin Yan, Haochen Wang, Jie Liu, XiaoLong Jiang, Yao Hu, Xu Tang, Guoliang Kang, Efstratios Gavves
Click-based interactive segmentation aims to generate target masks via human clicking, which facilitates efficient pixel-level annotation and image editing.
2 code implementations • 22 Aug 2018 • Yang He, Xuanyi Dong, Guoliang Kang, Yanwei Fu, Chenggang Yan, Yi Yang
With asymptotic pruning, the information of the training set would be gradually concentrated in the remaining filters, so the subsequent training and pruning process would be stable.
1 code implementation • 13 Apr 2019 • Guoliang Kang, Jun Li, DaCheng Tao
Dropout has played an essential role in many successful deep neural networks, by inducing regularization in the model training.
no code implementations • ECCV 2018 • Guoliang Kang, Liang Zheng, Yan Yan, Yi Yang
Second, we estimate the posterior label distribution of the unlabeled data for target network training.
no code implementations • 22 Sep 2017 • Xuanyi Dong, Guoliang Kang, Kun Zhan, Yi Yang
For most state-of-the-art architectures, Rectified Linear Unit (ReLU) becomes a standard component accompanied with each layer.
Ranked #12 on Image Classification on SVHN
no code implementations • 22 Jul 2017 • Guoliang Kang, Xuanyi Dong, Liang Zheng, Yi Yang
This paper focuses on regularizing the training of the convolutional neural network (CNN).
no code implementations • 1 Feb 2020 • Lijun Yu, Peng Chen, Wenhe Liu, Guoliang Kang, Alexander G. Hauptmann
To deal with the aforementioned problems, in this paper, we propose a training-free monocular 3D event detection system for traffic surveillance.
no code implementations • 17 Jan 2022 • Mengshu Sun, Haoyu Ma, Guoliang Kang, Yifan Jiang, Tianlong Chen, Xiaolong Ma, Zhangyang Wang, Yanzhi Wang
To the best of our knowledge, this is the first time quantization has been incorporated into ViT acceleration on FPGAs with the help of a fully automatic framework to guide the quantization strategy on the software side and the accelerator implementations on the hardware side given the target frame rate.
no code implementations • 28 Nov 2022 • Xiaoyue Duan, Guoliang Kang, Runqi Wang, Shumin Han, Song Xue, Tian Wang, Baochang Zhang
Based on this observation, we propose a simple strategy, i. e., increasing the number of training shots, to mitigate the loss of intrinsic dimension caused by robustness-promoting regularization.
no code implementations • CVPR 2023 • Guangrui Li, Guoliang Kang, Xiaohan Wang, Yunchao Wei, Yi Yang
With the help of adversarial training, the masking module can learn to generate source masks to mimic the pattern of irregular target noise, thereby narrowing the domain gap.
no code implementations • CVPR 2023 • Runqi Wang, Xiaoyue Duan, Guoliang Kang, Jianzhuang Liu, Shaohui Lin, Songcen Xu, Jinhu Lv, Baochang Zhang
Text consists of a category name and a fixed number of learnable parameters which are selected from our designed attribute word bank and serve as attributes.
no code implementations • 1 Nov 2023 • Yuxiang Bao, Di Qiu, Guoliang Kang, Baochang Zhang, Bo Jin, Kaiye Wang, Pengfei Yan
As a result, the corresponding regions across the adjacent frames can share closely-related query tokens and attention outputs, which can further improve latent-level consistency to enhance visual temporal coherence of generated videos.
no code implementations • 22 Dec 2023 • Xiaoyue Duan, Shuhao Cui, Guoliang Kang, Baochang Zhang, Zhengcong Fei, Mingyuan Fan, Junshi Huang
Consistent editing of real images is a challenging task, as it requires performing non-rigid edits (e. g., changing postures) to the main objects in the input image without changing their identity or attributes.